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About the TeamOpenAI is at the forefront of artificial intelligence, driving innovation and shaping the future with cutting-edge research. Our mission is to ensure that AI's benefits reach everyone. We are looking for visionary Research Engineers to join our Applied Voice Team, where you'll conduct groundbreaking research on speech models and transform it into real-world applications that can change industries, enhance human creativity, and solve complex problems.About the RoleAs a Research Engineer in OpenAI's Applied Voice Team, you will have the opportunity to work with some of the brightest minds in AI. You'll design and build state-of-the-art speech models (speech-to-speech, transcribing, text to speech, etc.) and help turn research breakthroughs into tangible solutions in B2B applications, API and ChatGPT AVM. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark.In this role, you will:Innovate and Build: Design and build advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact.Collaborate with the Best: Work closely with software engineers, product managers and forward deployed engineers to understand complex business challenges, address customer concerns and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives.Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches.Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large.You might thrive in this role if you:Master's/ PhD degree in Computer Science, Machine Learning, or a related field.2+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies.Demonstrated experience in deep learning and transformers modelsProficiency in frameworks like PyTorch or TensorflowStrong foundation in data structures, algorithms, and software engineering principles.Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimizationExperience with speech models is a plus.Excellent problem-solving and analytical skills, with a proactive approach to challenges.Ability to work collaboratively with cross-functional teams.Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlinesEnjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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Crusoe's mission is to accelerate the abundance of energy and intelligence. We’re crafting the engine that powers a world where people can create ambitiously with AI — without sacrificing scale, speed, or sustainability.Be a part of the AI revolution with sustainable technology at Crusoe. Here, you'll drive meaningful innovation, make a tangible impact, and join a team that’s setting the pace for responsible, transformative cloud infrastructure.About the Role As a Senior Staff Cloud Support Engineer, you are a technical authority within Crusoe Cloud and a force multiplier across Customer Experience, SRE, Networking, Fleet, and Product teams. You operate beyond ticket resolution. You design reliability guardrails, influence architecture decisions, mentor senior engineers, and directly protect revenue by preventing large-scale incidents. You bring deep expertise in Linux systems, Kubernetes, networking, and AI/ML infrastructure, and apply that knowledge with strong customer focus. You are comfortable operating in ambiguity, leading incident response, and shaping how Crusoe scales high-performance AI infrastructure globally. What You’ll Be Working On Technical Leadership & EscalationsServe as highest-level escalation point for complex P1/P0 incidents.Lead cross-functional root cause investigations involving compute, networking (IB/RDMA/RoCE), storage, and orchestration layers.Partner with SRE, Software teams (Storage, Networking, Compute, K8) to design systemic fixes rather than recurring workarounds.Reliability ArchitectureDesign and improve node validation, burn-in processes, performance baselining, and release readiness.Influence Kubernetes architecture, workload orchestration (Slurm, Terraform), and AI/ML cluster stability.Reduce MTTR and incident recurrence through structural improvements.AI/ML Infrastructure ExpertiseTroubleshoot NCCL, IB, GPU driver/firmware issues, distributed training failures.Support complex AI workloads (training + inference) with performance tuning and observability improvements.Customer-Facing AuthorityAct as senior technical advisor during high-risk customer incidents.Deliver executive-ready RCAs with clarity and confidence.Drive trust through transparency and technical depth.Mentorship & StandardsMentor P3/P4 engineers.Define SOPs and technical standards for support excellence.Partner with Enablement to raise the technical bar across the organization. What You Bring8+ years experience in SRE, DevOps, HPC, or Cloud Infrastructure roles.Advanced Linux systems expertise.Deep Kubernetes operational experience (CKA-level or higher).Strong networking knowledge: Infiniband, RDMA, RoCE, SDN.Experience supporting AI/ML workloads at scale (GPU clusters).Proven track record of resolving multi-layer, distributed system failures.Strong customer communication and executive-facing presence.BenefitsIndustry competitive payRestricted Stock Units in a fast growing, well-funded technology companyHealth insurance package options that include HDHP and PPO, vision, and dental for you and your dependentsEmployer contributions to HSA accounts Paid Parental Leave Paid life insurance, short-term and long-term disability Teladoc 401(k) with a 100% match up to 4% of salaryGenerous paid time off and holiday scheduleCell phone reimbursementTuition reimbursementSubscription to the Calm appMetLife LegalCompany paid commuter benefit; $300/monthCompensation RangeCompensation will be paid in the range of up to $180,000 -$220,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicants knowledge, education, and abilities, as well as internal equity and alignment with market data.Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

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About ClarionAt Clarion, we’re rebuilding how healthcare communicates in the age of AI.Today, clinics miss 30–40% of patient calls, while staff are overwhelmed by administrative work. We believe AI agents should handle these workflows—scheduling, billing, prescription refills, and follow-ups—so healthcare teams can focus on actual patient care.We’re building the communication infrastructure modern healthcare needs. Our AI agents don’t just answer calls—they complete workflows end-to-end, ensuring patients never go unheard. To date, we’ve handled hundreds of thousands of patient interactions across virtual care companies, health systems, and a $5B health insurance company.Clarion was founded by a Stanford/Harvard-trained physician (founding team at Two Chairs and Ophelia) and an ex-Amazon Alexa engineer who led AI/ML teams at Salesforce. We’ve raised $5.4M from Accel, Y Combinator, Sequoia (Scout), and leading healthcare founders. We’re an in-person team in New York, moving fast to solve one of healthcare’s most critical problems.Why This Role Is SpecialReal traction, early-stage impact: Dozens of paying customers, rapidly growing revenue, and the opportunity to own foundational backend systems at a critical inflection point.Mission-critical problem: Healthcare communication failures affect millions daily—your work directly powers systems patients and providers rely on.Elite technical context: Work closely with founders who deeply understand both healthcare operations and large-scale AI systems, enabling fast decisions and real ownership.What You’ll OwnCore backend systems: Design, build, and own the services, data models, and business logic powering Clarion’s AI agents and healthcare workflows.Workflow orchestration: Build infrastructure for multi-step, asynchronous workflows—including agentic AI workflows with conditional logic, retries, and graceful failure handling.Healthcare integrations: Own high-stakes integrations with EHRs and legacy healthcare platforms via APIs and RPA.Platform foundations: Create internal abstractions and tooling that allow the team to deploy and customize AI assistants for new customers quickly and reliably.Security and compliance: Implement and maintain backend authentication, authorization, and HIPAA-compliant architecture required for enterprise healthcare.Interesting Technical ChallengesGenerative AI at Scale: Design and operate production systems using LLMs with real-time monitoring, safety controls, and enterprise reliability.Agentic workflows: Architect backend systems that coordinate AI agents across complex healthcare workflows with strong guarantees.Enterprise reliability: Build systems supporting thousands of concurrent patient interactions with high uptime and fast incident detection.Fragmented healthcare systems: Design resilient abstractions across modern APIs and legacy EHRs while maintaining security and compliance.What We’re Looking For5+ years of experience designing, building, and scaling backend systems in high-reliability production environments.Strong backend expertise across APIs, relational databases, async workflows, and distributed systems.High ownership and agency—you thrive in ambiguity and take responsibility for system outcomes.Ability to communicate clearly, collaborate cross-functionally, and surface risks early.Bonus: experience with security, auth, or regulated environments (HIPAA familiarity is a plus).You’ll be a great fit if you enjoy owning critical backend systems end-to-end, solving complex problems under real-world constraints, and building infrastructure that directly impacts patient care.Interview ProcessWe move quickly and communicate clearly at every stage:Intro Chat (30 min, Virtual): Background, role context, and mutual fit.Technical Deep Dive (1 hr, Virtual): Backend systems and architecture with the CTO and a senior engineer.Onsite Team Day (Half Day, NYC): Collaborate on real problems, present a past project, meet the team, and assess mutual fit.Decisions are typically made within 24 hours of each stage.

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Who are we?Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like content generation, semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.Join us on our mission and shape the future!Cohere Labs is the dedicated research arm of Cohere. Our mission is to push machine learning forward through open, collaborative research and hands-on experimentation. We work on frontier problems in NLP and AI while creating space for researchers and engineers from different backgrounds to contribute, learn, and grow.We care about building things that are both thoughtful and useful, from new methods and datasets to tools that make research more accessible. Our team values curiosity, ownership, and practical impact over hype.Why join Cohere Labs?Cohere Labs brings together researchers and engineers to explore ambitious ideas and turn them into real systems. We focus on advancing machine learning while expanding access to applied research training and global collaboration.We pursue this mission in two ways:Creating open, collaborative research spaces where engineers and researchers work side-by-side on ambitious ML problems.Expanding access to applied research training, helping early-career engineers grow into strong research contributors.About the roleWe’re looking for Research Engineers who enjoy getting their hands dirty: building experiments, debugging models, scaling training pipelines, and turning research ideas into working systems. This is a highly practical role. You’ll work closely with scientists and other engineers to implement new methods, run large-scale experiments, and help shape the infrastructure that supports our research programs.You don’t need to have everything figured out yet. We care more about curiosity, strong fundamentals, and a willingness to learn quickly in a fast-moving research environment. You may be a fit if you:Have a strong engineering background in machine learning, NLP, or related areas (through a Master’s degree, industry experience, or equivalent hands-on work).Enjoy writing clean, reliable code and building systems that others can use and extend.Are comfortable experimenting, running ablations, analyzing results, and iterating quickly.Have experience with deep learning frameworks and model optimization techniques (PyTorch, distributed training, RLHF, finetuning, evaluation frameworks)Like collaborating closely with researchers and translating ideas into practical implementations.Are excited to grow your research instincts while staying grounded in engineering excellence.At Cohere Labs, research engineers are not just support roles. They are core contributors who help define how ideas become reality. If you want to work on meaningful problems, learn fast, and help build tools that shape the future of AI, we’d love to hear from you.If some of the above doesn’t line up perfectly with your experience, we still encourage you to apply! We value and celebrate diversity and strive to create an inclusive work environment for all. We welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.Full-Time Employees at Cohere enjoy these Perks:🤝 An open and inclusive culture and work environment 🧑‍💻 Work closely with a team on the cutting edge of AI research 🍽 Weekly lunch stipend, in-office lunches & snacks🦷 Full health and dental benefits, including a separate budget to take care of your mental health 🐣 100% Parental Leave top-up for up to 6 months🎨 Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement🏙 Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend✈️ 6 weeks of vacation (30 working days!)

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About the Role: We are looking for an GTM Engineer where you won’t just be using our tools—you’ll be the "First Customer," building the AI-native systems that power our technical support, onboarding, and customer success engines.You will own the technical roadmap for how LangChain supports its users. Your goal is to drive massive case deflection and a premium onboarding experience by building autonomous agents that solve complex technical problems before a human ever needs to step in. This is a role for a builder-operator who can identify a friction point in the customer journey and ship a production-grade agentic solution to fix it.You Will:Architect Customer Agents: Design and deploy production-grade agents (using LangGraph and LangSmith) that handle technical support queries, troubleshoot integrations, and guide users through complex onboarding flows.Drive Case Deflection: Analyze customer friction points and build self-service AI systems that significantly reduce support volume while improving the quality of the customer experience.Own the Domain: Act as the product owner and the technical muscle proactively identifying opportunities for improvement, propose architectures, and own the full lifecycle of the systems you build.Dogfood the Stack: Be a key member of the feedback loop for our product team. As you build complex systems for our customers, you’ll identify gaps in our frameworks and contribute back to the LangChain and LangGraph open-source ecosystem.Build Onboarding Workflows: Develop "AI-native onboarding" experiences that help enterprise customers move from prototypes to production faster by automating documentation retrieval and code generation.What we are looking for:AI-Native Developer: You have a deep understanding of the LLM stack: prompting, retrieval (RAG), cognitive architectures, and agentic loops. You have likely already built with LangChain or LangGraph.Engineering Foundation: You are a strong software engineer (typically 3+ years) with at least 1 year of experience specifically shipping LLM systems in production.Self-Directed "Founder" Mentality: You don't need a ticket to tell you what to fix. You are comfortable navigating ambiguity, identifying high-impact problems, and driving them to completion autonomously.Full-Stack Capability: Strong coding skills in Python or TypeScript (ideally both) and the ability to build end-to-end applications.Customer-Centric: You enjoy the intersection of high-level engineering and direct customer impact. You can translate a customer's technical pain point into a scalable system architecture.Nice to Haves:Expertise with LangSmith for evaluation and monitoring.Experience building or maintaining open-source projects.A background in technical consulting, solutions engineering, or high-growth GTM teams.Compensation:We offer competitive compensation that includes base salary, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance.Salary: $160K - $180K

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[MS/PhD Intern] AI Engineer (3개월/정규직 전환형)카메라 기반 End-to-End 자율주행과 Physical AI를 경험할 수 있는 기회! 42dot은 자율주행 기술 'Atria AI'를 개발하고 있으며, 2027년 말 레벨2+ 자율주행 기술이 양산 차량에 적용될 예정입니다. 끈질긴 집요함과 빠른 실행력으로 세상을 바꿀 인재를 기다립니다.Autonomous Driving Engineering42dot은 카메라 기반의 End-to-End 방식의 자율주행 소프트웨어와 저전력·고성능 임베디드 시스템을 개발하고 있으며, 최신 MLOps 시스템으로 자동화된 데이터 파이프라인을 구축했습니다. 또한 agile한 개발 프로세스를 통해 AI 모델 학습부터 실도로 검증 실험을 빠른 템포로 진행합니다.Role Overview 본 포지션은 Autonomous Driving Group의 정규직 전환형 Intern (MS/PhD) 으로, 연구 결과를 실제 양산 자율주행 시스템으로 연결하는 실전형 연구·개발 인턴십입니다.인턴십 기간 동안 단순 보조 업무가 아닌, 실제 양산을 목표로 하는 자율주행 시스템과 실차 데이터, 프로덕션 레벨의 코드 및 MLOps 환경을 기반으로 정규직 엔지니어와 동일한 수준의 문제를 End-to-End로 함께 해결합니다.What You'll Do 자율주행 시스템 핵심 기술에 대한 설계, 구현, 검증까지 End-to-End 수행실차 데이터 기반 알고리즘/모델 설계 및 검증시뮬레이션 및 실도로 실험을 통한 성능 분석 및 개선연구 결과를 실제 시스템에 적용 가능한 형태로 구현AD Group 내 실제 프로덕션 팀과의 긴밀한 협업을 통한 문제 해결Available Tracks최종 소속과 업무는 인턴십 및 인터뷰 과정에서 확인된 개인의 전문성, 연구 관심사 및 성장 방향과 조직별 니즈를 종합적으로 고려하여 결정될 예정입니다.[Physical AI]자율주행을 위한 인지(Perception) 및 행동 예측 ML 모델 구현 및 실험주행 데이터 전처리 및 학습 데이터셋 구성·분석모델 성능 평가 및 실험 결과 분석Failure Case 정리 및 성능 개선을 위한 실험[Sensor Fusion]카메라 등 센서에서 생성된 인지 결과를 활용한 Object-level Fusion 및 Tracking 구현실차 데이터 기반 Fusion 성능 분석 및 로그 분석C++ 기반 실시간 시스템에서 Fusion 로직 구조 이해 및 개선[SLAM]자율주행을 위한 SLAM 및 Localization 알고리즘 연구 및 개발카메라, IMU 등 센서 데이터를 활용한 기본적인 위치 추정 및 맵 생성실차 또는 시뮬레이션 데이터 기반 정확도·안정성 분석[AI Infrastructure]자율주행 및 ADAS 시스템을 위한 미들웨어 및 시스템 소프트웨어 설계·개발Linux 기반 환경에서 차량 소프트웨어 통합 및 디버깅·테스트 지원시뮬레이션, 자동화 스크립트 등 개발·검증 환경 구축 및 고도화[Data Platform]자율주행 데이터 수집, 처리, 분석 파이프라인 설계·개발모델 학습 및 평가 자동화를 위한 Data Flywheel 구축주행 로그 및 실험 결과 등 대규모 로그 분석을 통한 자율주행 성능 개선대규모 데이터셋을 관리하고 제공하기 위한 확장 가능한 자율주행 데이터 플랫폼 구축[VLA]자율주행 판단 및 제어를 위한 Vision-Language-Action(VLA) 모델 아키텍처 연구Triplane, Flex 등 다양한 Encoder 구조 실험 및 멀티모달 데이터 기반 모델 학습과 주행 판단 근거 (Rationale) 분석Open/Closed-loop 시뮬레이션 환경에서의 모델 검증 및 Failure Case 분석학습·평가 파이프라인 구축 및 Model/Simulation/Data 등 유관 부서와의 협업을 통한 End-to-End 연구 수행Interview Process서류전형 - 코딩테스트 - 1차 인터뷰 - 2차 인터뷰 - 최종합격전형절차는 직무별로 다르게 운영될 수 있으며, 일정 및 상황에 따라 변동될 수 있습니다.전형일정 및 결과는 지원서에 등록하신 이메일로 개별 안내드립니다.Additional Information본 포지션은 채용 연계형 인턴십으로, 인턴십 평가 결과에 따라 정규직 전환 여부를 검토합니다.인턴십은 3개월간 운영되며, 해당 기간 동안 full-time 근무를 원칙으로 합니다.정규직 전환 시에는 인턴십 종료 후 1개월 이내 입사가 가능해야 하며, 조정이 필요한 경우 별도 협의를 통해 결정할 수 있습니다.석사·박사과정 졸업 예정자 및 기졸업자, 또는 경력 1년 미만의 인원에 한하여 지원할 수 있습니다.전문연구요원의 경우, 전직이 가능한 대상자에 한해 지원할 수 있습니다.이력서 제출 시 주민등록번호, 가족관계, 혼인 여부, 연봉, 사진, 신체조건, 출신 지역 등 채용절차법상 요구 금지된 정보 및 학교 또는 연구실의 연구 비밀을 침해하는 내용이 없도록 유의하시기 바랍니다.모든 제출 파일은 30MB 이하의 PDF 양식으로 업로드를 부탁드립니다. (이력서 업로드 중 문제가 발생한다면 지원하시고자 하는 포지션의 URL과 함께 이력서를 recruit@42dot.ai으로 전송 부탁드립니다.)인터뷰 프로세스 종료 후 지원자의 동의하에 평판조회가 진행될 수 있습니다.장애인/보훈대상자는 관련 법령에 따라 우대합니다.해외 국적자의 경우, 체류 자격 상 정규직 입사가 가능한 분을 대상으로 합니다.제출한 지원서에 허위 사실이 포함된 경우, 합격이 취소될 수 있습니다..※ 지원 전 아래 내용을 꼭 확인해 주세요.42dot이 일하는 방식, 42dot Way 보러가기 →42dot만의 업무몰입 프로그램, Employee Engagement Program 보러가기 →

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About UsHarmattan AI is a next-generation defense prime building autonomous and scalable defense systems. Following the close of a $200M Series B, valuing the company at $1.4 billion, we are expanding our teams and capabilities to deliver mission-critical systems to allied forces.Our work is guided by clear values: building technologies with real-world impact, pursuing excellence in everything we do, setting ambitious goals, and taking on the hardest technical challenges. We operate in a demanding environment where rigor, ownership, and execution are expected.About the RoleAs a Multi-Agents Mission Planning Engineer, you’ll design and implement the Guidance, Navigation, and Control algorithms that translate high-level mission goals into actionable guidance for autonomous robots and multi-agent systems. You’ll bridge cutting-edge research and field-ready autonomy, ensuring our systems are both intelligent and predictable in live operations.ResponsibilitiesDesign algorithms that decompose high-level missions into structured, solvable guidance tasks for autonomous robots.Develop and optimize mission and path-planning frameworks for autonomous systems.Build scalable backend integrations for mission guidance and execution.Run simulations and validation campaigns to assess autonomy consistency across diverse mission types.Partner with AI/ML, backend, and product teams to ensure algorithms are efficient, testable, and deployable in real-time environmentCandidate RequirementsEducation: Ph.D. or M.S. in Aerospace Engineering, Robotics, Applied Math, AI, or related field. A PhD in the field of multi-agent systems or reinforcement learning is a huge plus.Experience designing and deploying mission- or path-planning algorithms in aerospace, defense, or robotics is a huge plusTechnical Skills: Strong coding in Python and C++ . Deep understanding of autonomous decision-making, multi-agent coordination, and simulation frameworks.Mindset: Ability to move from research prototype to production-grade systemCommitment: 100% dedication to Harmattan AI’s mission, vision, and ambitious growth plans, ready to go the extra mile to ensure operational excellence.We look forward to hearing how you can help shape the future of autonomous defense systems at Harmattan AI.

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About the teamOpenAI’s Forward Deployed Engineering (FDE) org sits at the intersection of product, engineering, research, and go-to-market. We take frontier platform capabilities into the real world with design partners, turning raw customer signal into shipped software, repeatable patterns, and product direction.This group is an innovation loop within FDE. We sprint on a small number of platform bets at a time: identify high-signal problems emerging across deployments, build early versions quickly, validate them with design partners, and work with our core engineering and product counterparts to put successful bets on a scalable path. When a capability is ready to scale, we help transition ownership — and then move on to the next frontier.About the rolePlatform Incubation Engineer is a role within Forward Deployed Engineering (FDE) for strong software and ML engineers who want to build new platform capabilities from scratch, grounded in real customer deployments.You’ll join a small team working in pods against platform bets rather than a single long-running account. You’ll collaborate closely with customer-tagged FDEs and partner teams across engineering and product to: (1) incubate early versions, (2) validate them with design partners through short deployments or pilots, and (3) drive adoption by making the capability durable, usable, and ready to scale. You should expect to be customer-facing when it matters – pitching, rollout planning, debugging, and learning directly from what breaks in production – but your primary charter is to turn frontier signal into reusable platform capability.This role does not require travel. It is based in San Francisco or New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel is optional-by-project and typically <10%, with occasional spikes for key embeds or launches.In this role you willArchitect and build new platform capabilities: turn frontier customer signal into concrete designs, implementations, and APIs that become part of the OpenAI platform.Incubate platform bets end-to-end: take ambiguous problems, form a crisp hypothesis, ship an initial capability, and iterate quickly based on what breaks in real usage.Embed with design partners to learn fast: get close to production constraints, run deep technical discovery, and translate needs into product and platform requirements.Partner with customer-tagged FDEs in the field: deploy and debug together, capture repeatable patterns, and convert field learnings into platform improvements.Design and run pilot programs: define qualification criteria for early adopters, stand up internal/external alphas, and use pilots to harden both the platform and the rollout playbook.Collaborate as part of cross-functional platform teams: partner closely with core product and engineering counterparts, often as a single virtual team, to align on architecture and get to production together.Drive adoption outcomes: measure usage, identify blockers and failure modes, and prioritize the next platform increments that unlock repeatable value.You might thrive in this role if youBring 5+ years of software engineering or ML engineering experience with a track record of shipping 0→1 capabilities that other engineers or customers depend on. Experience in high-ambiguity, fast-iteration environments (startups or product-centric teams) is a plus.Have owned customer-adjacent technical work end-to-end, from scoping and hypothesis-setting through production adoption, and improved outcomes through structured iteration (instrumentation, evals, error analysis, and tightening success criteria over time).Have built or operated systems where reliability, security, and governance materially shaped design (permissions/RBAC, auditability, data access boundaries, rollout safety, observability, and incident-driven hardening).Communicate clearly across engineering, product, go-to-market, and executive audiences, simplifying complex ideas and translating technical tradeoffs into adoption impact, sequencing decisions, and measurable outcomes. You can credibly “pitch” a platform bet in a customer conversation.Default to systems thinking: you turn ambiguous feedback, failures, and escalations into durable product requirements and reusable platform capabilities, not one-off fixes or bespoke delivery work.About OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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About Terra AIWe are building the state-of-the-art AI platform for the discovery and development of clean energy and mineral resources. We bring the most advanced techniques in generative AI, foundation modeling, and autonomous decision optimization to tackle the most important problems in the geosciences. These systems can help more reliably identify critical resource deposits, more rapidly measure and characterize them, and design more efficient and sustainable production plans.We are backed by Khosla Ventures and other leading venture investors. We are now looking to grow our team from ~15 to ~30 by the end of the year to continue to mature our technology and support deployment with our world-class mineral and clean energy partners.Role descriptionIn the same way image generators have shown the remarkable ability to produce a diverse set of realistic pictures conditioned on a text prompt (and other inputs), we are developing a generative model that produces 3D geological models conditioned on geophysical surveys, bore hole measurements, and other forms of physical observation. The outputs of the generative model capture what we know and don’t know about the state of the subsurface, allowing explorers to make maximally informed decisions about how and where to explore for critical resources. We are looking for a talented deep learning engineer or scientist to lead the development of this model that will revolutionize decision making in the earth subsurface for a wide range of clean energy applications.Role ResponsibilitiesDesign, train, test, and iterate on diffusion models for 3D geological modelsDesign, train, test, and iterate on an approach to for conditioning generation on geophysical data and other observationsInform the generation of synthetic data to improve model performanceAdapt diffusion modeling approach to specific real-world projects in collaboration with project teams. QualificationsRequired Qualifications:Extensive PyTorch ExperienceDeep understanding of PyTorch, including writing custom modules, optimizing training, and debugging issues in large-scale models.Expertise in Developing Large Deep Learning Models from ScratchProven ability to design, implement, and train complex deep learning architectures from the ground up.Data Curation SkillsHands-on experience in creating, cleaning, and maintaining high-quality datasets tailored for machine learning applications.Strong Software Engineering and Design ExperienceProficient in software development best practices, including version control, testing, and code optimization.Familiarity with designing scalable and maintainable systems.Bonus points if you:Experience with Generative ModelsFamiliarity with generative architectures, particularly diffusion models, and an emphasis on posterior sampling methods.Knowledge of Transformer ArchitecturesExperience building and training transformers, especially in applications involving 3D data.Scaling Models Across Large GPU ClustersExpertise in parallelizing models across multiple GPUs and optimizing distributed training pipelines.Cloud Infrastructure ExpertiseExperience setting up, managing, and optimizing cloud environments for machine learning workloads, including provisioning resources and managing costs.

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About AdaptiveNVIDIA and OpenAI’s only AI cybersecurity investment.Adaptive is a cybersecurity startup on a mission to stop AI-powered cyberattacks. In December 2025, the company announced an $81M Series B led by NVIDIA and Bain Capital Ventures, with participation from Capital One Ventures, Citi Ventures, and continued support from Andreessen Horowitz (a16z), the OpenAI Startup Fund, and Abstract Ventures. The round marked NVIDIA’s first AI cybersecurity investment.Adaptive was founded by Brian Long and Andrew Jones, repeat entrepreneurs who have built and scaled category-defining companies. Brian and Andrew previously co-founded Attentive, which grew to more than $500M in annual revenue and a $10B+ valuation, and TapCommerce, which was acquired by Twitter. Together, they bring deep experience building high-growth, product-led businesses at massive scale as Adaptive builds the security layer for the AI era.Trusted by leading banks, technology companies, and healthcare organizations, Adaptive protects teams from emerging threats like deepfakes, smishing, and AI-powered voice scams. With rapid enterprise adoption and a $200B+ market ahead, the company is just getting started.RoleWe are seeking a Staff ML Engineer to define and build Adaptive's ML capabilities. Adaptive is an AI cybersecurity company whose products use LLMs and ML models to detect, classify, and respond to threats in real time. ML is central to the future of our products, and we need someone who can own the strategy, infrastructure, and execution for how we use it.We don't have dedicated ML infrastructure or an ML team today. You'll be building this from the ground up. You'll set the technical direction for how we use ML across the company, stand up the infrastructure, and do the hands-on work yourself.ResponsibilitiesDefine Adaptive's ML strategy: where ML should be applied across our products, what infrastructure we need, and how we should approach build vs. buy decisions.Design and build production ML systems end-to-end — data pipelines, model training, evaluation frameworks, and inference serving.Establish evaluation methodology. Define how we measure model quality, catch regressions, and make data-driven decisions about model changes.Own the strategy for getting the data you need, in the format you need it — what/how to label, how to build feedback loops, and how our models improve over time.Partner with product engineers to integrate ML into the product. You will write production code and work within our existing codebase.Over time, help build and lead the ML team as scope grows.Qualifications8+ years of experience building ML systems in production, ideally with experience standing up the ML function at an early stage startup or as the senior or lead ML person at a previous company.Strong software engineering fundamentals. You write production-quality code in modern languages (Python, Java, TypeScript) and work within large codebases.Experience with cloud ML infrastructure (AWS SageMaker, Bedrock, Modal, Baseten, or similar).Experience with common ML and data processing frameworks (PyTorch, Tensorflow, Spark)Comfortable working across the stack — infrastructure, backend services, and data systems.Track record of mentoring MLEs and other engineers with observable, clear improvements in those you've worked with.High autonomy. You'll have support and context from leadership, but you're expected to define the path forward and drive it.

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We’re reinventing personal transportation—making the future safer, cleaner, and more enjoyable. We’ve created our vehicle specifically for dense, complicated urban environments. Zoox is the only driving vehicle on the market with bidirectional driving capabilities and four-wheel steering, allowing us to maneuver through compact spaces and change directions without the need to reverse. The future is for riders! Our growing software engineering leadership team is searching for a Senior Manager of Perception. Our perception stack is responsible for building Zoox’s world-class 3D environment model from multi-modal sensor data. We create novel AI architectures that combine the latest academic results with many in-house innovations in creative ways. Our algorithms are relentlessly optimized and tuned to run efficiently and effectively on a wide variety of real-life data as well as in simulation. You will be responsible for leading high-impact Perception teams with their technical roadmap and milestone goals. You will be closely collaborating with other AI and SW leaders, simulation, and our systems design and mission assurance teams to deliver an exceptional dynamic objects perception system encompassing modalities such as vision, lidar, radar and long-wave IR across pipelines such as segmentation, detection, classification, fusion and tracking. You will lead a diverse, experienced team with a rapidly growing scope and responsibility while also working on some of the most complex problems in artificial intelligence, perception, and sensor fusion. In this role, you will:Build and lead a group of managers and engineers, and be responsible for the team’s roadmap, productivity, execution and impact within the company.Set the vision for, grow, and lead a team of talented software engineers in the overall planning, execution, and success of complex technical projects, while providing the team with technical leadership.Collaborate with engineers and leaders across a variety of teams to brainstorm and accelerate the development of perception capabilities.Provide clear summaries, progress, and recommendations to our executive leadership team.Establishing best practices and statistical rigor around data-driven decision-making.Stay on top of industry and academic trends in AI and perception, making sure Zoox remains at the cutting edge of both algorithms and their implementation at scale.QualificationsStrong understanding of computer vision systems and AI software stacks.5+ years of extensive leadership experience, leading teams of 20+10+ years of experience in computer vision, machine learning and related technologies.Strong leadership skills suitable for recruiting, leading, growing, and managing technical team members in solving a challenging problem, and building a critical component of a real-time system.Recent experience in implementing vision & perception algorithms.Expertise in implementing autonomy solutions and deploying real-world systems.Experience with recent AI approaches including E2E models for perception, transformers and sparse networks.Experience with sensor fusion and uncertainty modeling across multiple modalities.Strong presentation and communication skills.MSc or PhD in Robotics, Computer Science or related fields.Bonus QualificationsFamiliarity with perception of autonomous vehicles or similar robotsHands-on experience having deployed real products or platforms into the real world, and intimately understanding the challenges of working with complex systemsInvolvement in validation or evaluation of risk and/or safety-critical systemsKnowledge of GPU and/or TPU programming (CUDA, TensorRT, etc.) 277,000 - 389,000 a yearBase Salary Range There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position. Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.

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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 1000+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started. Role OverviewAs a Engineering Manager, Product at Harvey, you’ll play a pivotal role in shaping the foundation of our product platform while directly building user-facing features for some of the world’s leading law firms and enterprise customers. This team owns and operates the platform layer that enables secure, reliable, and flexible experiences for our customers including notifications, permissions and feature flag infrastructure. We also build enterprise-grade collaboration product experiences for law firms.You will design and own systems that not only serve as critical infrastructure for the rest of the company, but also directly impact how our users engage with Harvey’s AI-powered legal tools. This role is ideal for engineers who are excited by the opportunity to move between deep platform thinking and hands-on product iteration.This role is based in Toronto, Canada. We use a hybrid, 3+ days-per week in-person work model and offer relocation assistance to new employees.What You'll Do Own end-to-end delivery of core product initiatives, from technical design through execution and iteration, while directly managing a high-performing fullstack engineering team.Set technical direction for large-scale, AI-powered systems, including:Retrieval over petabyte-scale document collections.Product interfaces that enable organizations to collaborate with AI.Long-horizon (1000+ step) planning agents for mission-critical workflows.Government-grade security for highly sensitive data.Evaluation of LLMs across a 10k+ leaf taxonomy of tasks.Internet-scale data collection across 50+ jurisdictions.Translate product vision into architecture, making pragmatic tradeoffs that balance speed, quality, and long-term scalability in a fast-moving environment.Lead hands-on when it matters: contribute to design, code, and architecture reviews, and dive into implementation to unblock the team or tackle the hardest problems.Build and grow your team by hiring exceptional engineers, setting clear technical and behavioral standards, and investing in mentorship and career development.Partner deeply with Product, Design, and AI to identify high-leverage opportunities and ship highly intuitive, detail-oriented user experiences.Establish a strong engineering culture centered on simplicity, ownership, craftsmanship, and continuous improvement.Align execution with company goals, ensuring technical investments directly support product strategy and long-term impact.What You Have6+ years of experience as a product-focused fullstack or backend software engineer (post BS/MS), with a history of shipping real products to real users.2+ years of experience leading engineers, with clear ownership over both delivery and team health. Past management experience is a plus.A proven ability to design and operate backend platforms that support multiple product lines at scale.Strong experience with modern frontend frameworks (e.g. React) or backend systems (e.g. Python, Node, Go).Excellent technical judgment: you know when to move fast, when to invest, and when to simplify.A strong product instinct and attention to detail, with a track record of building intuitive, high-quality user experiences.Demonstrated success building, motivating, and retaining high-performing teams in high-growth environments.Solid computer science fundamentals and strong programming skills.Grit and ownership mindset — you’re comfortable operating in ambiguity and taking responsibility for outcomes.Bonus: experience with AI-powered applications, large-scale data systems, LLM evaluation, or complex internal platforms.What We OfferBe part of building something special as a founding member of our Toronto teamStructured hybrid working arrangement: 3 days in our Toronto office, 2 days working from home We are an AI company and we use AI to improve all of our processes, including in the recruitment process. Whilst we do use AI to help improve efficiency in our recruitment process, we do not rely on AI to make any automated decisions and ensure that a human reviews AI output.#LI-KT1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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About the TeamThe Safety Systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency.The Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety.About the RoleProviding access to powerful AI models introduces a host of challenging questions when it comes to model safety: How do we define safe behavior for how a model should behave? To what end? How do we do this in such a way that is actionable, objective and sustains replicability?This is a senior role in which you’ll help shape policy creation and development at OpenAI and make an impact by helping ensure that our groundbreaking technologies do not create harm. The ideal candidate can identify and develop cohesive and thoughtful taxonomies of harm on high risk topics with a sense of urgency. They can balance internal and external input in making complex decisions, carefully think through trade-offs, and write principled, enforceable policies based on our values. Importantly, this role is embedded in our research teams and directly informs model training.This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.In this role, you’ll:Design model policies that govern safe model behavior in an objective and defensible way - e.g. how should the model respond in risky/unsafe scenarios? What does unsafe mean? How do we achieve safety while preserving beneficial model capabilities?You will develop taxonomies that inform data collection campaigns, model behaviour and monitoring strategies and also toe the line between maximizing utility and preventing catastrophic risk.Lead prioritization for safety efforts across the company for new model launches, understanding and addressing technical and business trade-offs.Develop a broad range of subject matter expertise while maintaining agility across topics.You will work across many internal teams which will require high organizational acumen and confident decision making.You might thrive in this role if you:Have extensive experience researching LLMs, ML, AI, tech policy, moral reasoning, and/or enjoy classification problems.Have extensive experience defining, refining and enforcing policies for ML models across training, evaluation, and deployment.Understand the practical challenges of translating policy into model behavior across the full training stack, and can incorporate these constraints into policy design.Can reason about the benefits and risks of open-ended problem spaces, generate novel approaches under ambiguity, and take full ownership of end-to-end solutions from concept through execution.Most relevant publications:Introducing HealthBenchPreparing for future AI capabilities in biologySafety evaluations hubOpenAI GPT5 System CardEvaluating Fairness in ChatGPTImproving Model Safety Behavior with Rule-Based RewardsOpenAI Model SpecAbout OpenAIOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.OpenAI Global Applicant Privacy PolicyAt OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

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Why Faculty? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen.About the teamThe Faculty Frontier TM product is our ambitious vision to create the first enterprise-grade platform that unifies decision intelligence with AI Agents to optimise real-world outcomes of critical processes across large-scale organisations. You will work on highly complex and consequential problems across the real economy, with particular focus on healthcare and life sciences.About the roleJoin the Frontier team as a Senior Manager to help realise our vision of the first enterprise-grade decision intelligence platform. You will lead the delivery of AI-powered agents that optimise critical processes within global life sciences and healthcare. This is an entrepreneurial role for a strategic operator who can navigate complex technical landscapes, manage high-stakes enterprise accounts, and lead multidisciplinary teams to deliver real-world impact. You’ll be the bridge between our cutting-edge technology and the transformative outcomes our customers achieve.What you'll be doing:Leading transformational AI system implementations by scoping high-value solutions and navigating complex technical challenges alongside technical colleagues.Managing enterprise life sciences accounts, including oversight of pricing, contract negotiations, resourcing, and the identification of strategic growth opportunities.Building deep trust with senior stakeholders in global enterprises through a sophisticated understanding of how Frontier addresses their unique operational problems.Advocating for customer needs internally by providing the product development team with direct insights to refine and enhance the platform.Creating scalable delivery assets, such as playbooks and process improvements, to empower both external partners and internal teams.Collaborating across functions—including engineering, data science, and business development—to explore novel use cases and drive seamless project coordination.Who we're looking for:You bring extensive experience in technology consulting, product development, or a similar high-impact, customer-facing role.You have a proven track record of leading multidisciplinary teams to deliver technically complex projects, particularly those involving AI/ML technologies.You possess exceptional communication skills, with the ability to simplify complex technical concepts and foster trust with diverse stakeholders.You are an expert at managing senior customer relationships and influencing outcomes across multiple internal and external teams.You demonstrate a proactive and adaptable mindset, thriving in ambitious, fast-paced environments where you can find pragmatic paths through ambiguity.You are motivated by solving consequential problems and have the versatility to evolve your role as the Frontier product scales globally.Note: if you've got experience working in the Life Sciences sector that'd be awesome - this is a "nice to have though" and motivation to work in that space will more than suffice.Interview ProcessTalent Team Screen (30 mins)Hiring Manager Introduction (60 mins)Case Study Interview (90 mins)in-person Principles Interview (60 mins) #LI-PRIOOur Recruitment EthosWe aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.Some of our standout benefits:Unlimited Annual Leave PolicyPrivate healthcare and dentalEnhanced parental leaveFamily-Friendly Flexibility & Flexible workingSanctus CoachingHybrid Working (2 days in our Old Street office, London)If you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please do apply or reach out to our Talent Acquisition team for a confidential chat - talent@faculty.ai Please know we are open to conversations about part-time roles or condensed hours.

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About DecagonDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.Our technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.We’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.We’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.About the TeamThe Research team develops the model and decision-making stack that powers Decagon’s conversational agents for enterprise support. We research, adapt, and implement state-of-the-art techniques in model training, prompting, orchestration, and evaluation in order to make our agents more accurate, robust, and efficient in real-world deployments.Our goal is to push the frontier of applied conversational AI: agents that reliably understand nuanced intent, track long context, and take the right actions under uncertainty. We measure success the way customers feel it: higher resolution rates, better user satisfaction, and consistent behavior at scale.About the RoleAs a Senior Research Engineer, you’ll be responsible for building industry-leading conversational AI models that power Decagon’s agent, and taking them all the way from idea to production. You’ll own multi-quarter initiatives that push the agent’s reliability, capability, and efficiency forward, and you’ll design and implement frontier approaches for training, evaluation, and orchestration across the system.We’re looking for strong engineers who want to build the core models and algorithms behind our AI agents. People here own their work end-to-end, ship real improvements, and are trusted to make high-impact technical decisions.In this role, you willLead research and engineering efforts to improve core conversational capabilities in production, including instruction following, retrieval, memory, and long-horizon task completionBuild and iterate on end-to-end models and pipelines that optimize for quality, efficiency, and user experiencePartner with platform and product engineers to integrate new models into production systemsBreak down ambiguous research ideas into clear, iterative milestones and roadmaps.Your background looks something like this5+ years of experience in AI/ML engineering or research.Prior experience post-training and deploying LLMs in production environments.Fluency in Python and modern ML tooling (training, evaluation, data pipelines)Track record of taking research ideas from prototype → reliable, measurable production impactBenefitsMedical, dental, and vision benefitsTake what you need vacation policyDaily lunches, dinners and snacks in the office to keep you at your bestCompensation£200K – £300K + Offers Equity

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About xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.  About the Role As an Accounting Expert, you will be instrumental in enhancing the capabilities of our cutting-edge technologies by providing high-quality input and labels using specialized software. Your role involves collaborating closely with our technical team to support the training of new AI tasks, ensuring the implementation of innovative initiatives. You'll contribute to refining annotation tools and selecting complex problems from corporate accounting domains, with a focus on financial reporting, consolidation, internal controls, and GAAP compliance where your expertise can drive significant improvements in model performance. This position demands a dynamic approach to learning and adapting in a fast-paced environment, where your ability to interpret and execute tasks based on evolving instructions is crucial. AI Tutor’s Role in Advancing xAI’s Mission As an AI Tutor, you will play an essential role in advancing xAI's mission by supporting the training and refinement of xAI’s AI models. AI Tutors teach our AI models about how people interact and react, as well as how people approach issues and discussions in corporate accounting. To accomplish this, AI Tutors will actively participate in gathering or providing data, such as text, voice, and video data, sometimes providing annotations, recording audio, or participating in video sessions. We seek individuals who are comfortable and eager to engage in these activities as a fundamental part of the role, ensuring a strong alignment with xAI’s goals and objectives to innovate. Scope An AI Tutor will provide services that include labeling and annotating data in text, voice, and video formats to support AI model training. At times, this may involve recording audio or video sessions, and tutors are expected to be comfortable with these tasks as they are fundamental to the role. Such data is a job requirement to advance xAI’s mission, and AI Tutors acknowledge that all work is done for hire and owned by xAI. Responsibilities Use proprietary software applications to provide input/labels on defined projects.   Support and ensure the delivery of high-quality curated data.   Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies.   Interact with the technical staff to help improve the design of efficient annotation tools.   Choose problems from corporate accounting fields that align with your expertise, providing rigorous solutions and model critiques where you can confidently provide detailed solutions and evaluate model responses.   Regularly interpret, analyze, and execute tasks based on given instructions.   Key Qualifications Must have 3+ years of Big 4 public accounting experience (audit/assurance) on corporate or SEC clients, or an equivalent senior corporate accounting role (e.g., Controller, Assistant Controller, or Technical Accounting Manager at a public company or large private enterprise with complex GAAP reporting).   Must possess a Master's or PhD in Accounting (corporate focus) or equivalent as a licensed CPA.   Proficiency in reading and writing, both in informal and professional English.   Strong ability to navigate various corporate accounting information resources, databases, and online resources (e.g., FASB codification, SEC EDGAR, 10-K/10-Q filings, ERP systems).   Outstanding communication, interpersonal, analytical, and organizational capabilities.   Solid reading comprehension skills combined with the capacity to exercise autonomous judgment even when presented with limited data/material.   Strong passion for and commitment to technological advancements and innovation in corporate accounting.  Preferred Qualifications 5+ years at a Big 4 firm or in a senior corporate controllership role, with direct involvement in SEC reporting, SOX 404, or complex consolidations.   Experience drafting or reviewing 10-K/10-Q footnotes, MD&A, or technical accounting memos.   Possesses experience with at least one publication in a reputable accounting journal or outlet.   Teaching experience as a professor   Location & Other Expectations This position is based in Palo Alto, CA, or fully remote.   The Palo Alto option is an in-office role requiring 5 days per week; remote positions require strong self-motivation.   If you are based in the US, please note we are unable to hire in the states of Wyoming and Illinois at this time.   We are unable to provide visa sponsorship.   Team members are expected to work from 9:00am - 5:30pm PST for the first two weeks of training and 9:00am - 5:30pm in their own timezone thereafter.   For those who will be working from a personal device, please note your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later.   Compensation $45/hour - $100/hour The posted pay range is intended for U.S.-based candidates and depends on factors including relevant experience, skills, education, geographic location, and qualifications. For international candidates, our recruiting team can provide an estimated pay range for your location. Benefits: Hourly pay is just one part of our total rewards package at xAI. Specific benefits vary by country, depending on your country of residence you may have access to medical benefits. We do not offer benefits for part-time roles.xAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 1000+ customers in 58+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started.Role OverviewAs a senior member of our founding Forward Deployed Engineer (FDE) team, you’ll embed with Harvey’s enterprise customers (Am Law firms, in-house teams at large enterprises, and other professional services organizations) to turn cutting‑edge AI systems into production‑grade workflows that deliver measurable outcomes fast. You’ll move from prototype to deployment quickly, surface patterns from the field, and feed them back into Harvey’s platform and product roadmap. You’ll start from open‑ended, high‑leverage problems, design and implement end‑to‑end solutions with real users and data, and ship to production under tight feedback loops.This role is based in New York, NY. We use an in-person work model and offer relocation assistance to new employees..What You'll DoEmbed with customers to map out workflows, de‑risk constraints, and define crisp success metrics for custom builds.Design → prototype → productionize custom workflows: customize knowledge sources and retrieval pipelines, tool use/agents, prompts, and guardrails; then harden them for reliability, observability, and scale.Integrate workflows with clients systems (DMS, KM, ticketing, identity/SSO) and data sources; standing up secure connectors to the rest of the Harvey platform.Build and maintain evals & harnesses that capture real‑world quality on a client-by-client basis, wiring those signals into iteration loops and model choices.Operationalize adoption: run training, write crisp runbooks, and hand-off durable playbooks to customer champions—and to Harvey product/eng—so wins scale beyond one account.Surface field patterns (recurring prompts, tools, workflows, failure modes) that inform platform capabilities and future product bets.How you will make a 10x ImpactHigh Beta: You understand that volatility is the normal course of action, and you embrace it. You assume failure is the most likely outcome, so you fail fast and learn. You are transparent about failure, and you actively try to kill your own ideas by tackling the hardest problems first. You don’t subscribe to sunk costs.Unreasonable hospitality: You practice unreasonable hospitality, grounding your technical work in a deep obsession with the customer. You will spend as much time understanding the "why" from users as you do building the "what," ensuring our bets are aimed at solving real, meaningful problems.Action, action, and still more action: You live by a relentless bias for action. You believe progress is measured by what you build and learn, not what you discuss in meetings. You prioritize shipping and getting real-world feedback over perfecting a plan on paper.Contrarian, with common sense: You constantly think about what’s missing, not what’s working well today. You feel uncomfortable when an idea becomes consensus. But you match ambitious ideas with pragmatic execution. You find the most straightforward path to de-risk a complex concept, focusing on proving value quickly rather than over-engineering a solution.What You Have5+ years building and operating production software with meaningful 0→1 ownership and the ability to operate under ambiguity.Experience building LLM‑powered applications (retrieval, tools/agents, structured outputs, prompt/runtime safety) and taking them to production.Comfort working directly with customers—from scoping ambiguous problems to shipping, integrating, training, and iterating on adoption.Practical experience with evals (designing task suites, pipelines, and dashboards that reflect user quality); you use evals to drive model/product decisions.Clear, concise communication; low‑ego collaboration; appetite for in‑person pairing with teammates and customers in NYC.Compensation Range$200,000-$260,000 USD#LI-SB1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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We are looking for the bestAt 42dot, our AI Data Pipeline Engineer architect and scale global data pipelines that ingest and process data from worldwide sources. You will design and operate high-throughput systems to reliably deliver petabyte-scale data to our large-scale GPU infrastructure, powering mission-critical AI workloads.ResponsibilitiesDesign and build high-performance, scalable data pipelines to support diverse AI and Machine Learning initiatives across the organization.Architect and implement multi-region data infrastructure to ensure global data availability and seamless synchronization.Develop flexible pipeline architectures that allow for complex branching and logic isolation to support multiple concurrent AI projects.Optimize large-scale data processing workloads using Databricks and Spark to maximize throughput and minimize processing costs.Maintain and evolve the containerized data environment on Kubernetes, ensuring robust and reliable execution of data workloads.Collaborate with AI researchers and platform teams to streamline the flow of high-quality data into training and evaluation pipelines.QualificationsExtensive professional experience in building and operating production-grade data pipelines for massive-scale AI/ML datasets.Strong proficiency in distributed processing frameworks, particularly Apache Spark and the Databricks ecosystem.Deep hands-on experience with workflow orchestration tools like Apache Airflow for managing complex dependency graphs.Solid understanding of Kubernetes and containerization for deploying and scaling data processing components.Proficiency in distributed messaging systems such as Apache Kafka for high-throughput data ingestion and event-driven architectures.Expert-level programming skills in Python for system-level optimizations.Strong knowledge of cloud-native services and best practices for building secure and scalable data infrastructure.Logical approach to problem-solving with the persistence to identify and resolve root causes in complex, large-scale systems.Strong communication skills to effectively collaborate with cross-functional teams and external partners.Preferred QualificationsExperience in architecting global, multi-region data pipelines and solving challenges related to cross-border data transfer and latency.Practical experience or a strong interest in implementing distributed computing frameworks like Ray for AI workloads.Experience in building real-time or near-real-time pipelines using Spark Streaming or Flink.Familiarity with Infrastructure as Code (IaC) tools such as Terraform to manage complex data environments.Understanding of the end-to-end ML lifecycle (MLOps) and how data infrastructure supports model experimentation and deployment.Interview Process서류전형 - 온라인 코딩테스트 - 화상면접 (1시간 내외) - 대면면접 (3시간 내외) - 최종합격전형절차는 직무별로 다르게 운영될 수 있으며, 일정 및 상황에 따라 변동될 수 있습니다.전형일정 및 결과는 지원서에 등록하신 이메일로 개별 안내드립니다.Additional Information이력서 제출 시 주민등록번호, 가족관계, 혼인 여부, 연봉, 사진, 신체조건, 출신 지역 등 채용절차법상 요구 금지된 정보는 제외 부탁드립니다.모든 제출 파일은 30MB 이하의 PDF 양식으로 업로드를 부탁드립니다. (이력서 업로드 중 문제가 발생한다면 지원하시고자 하는 포지션의 URL과 함께 이력서를 recruit@42dot.ai으로 전송 부탁드립니다.)인터뷰 프로세스 종료 후 지원자의 동의하에 평판조회가 진행될 수 있습니다.국가보훈대상자 및 취업보호 대상자는 관계법령에 따라 우대합니다.장애인 고용 촉진 및 직업재활법에 따라 장애인 등록증 소지자를 우대합니다.42dot은 의뢰하지 않은 서치펌의 이력서를 받지 않으며, 요청하지 않은 이력서에 대해 수수료를 지불하지 않습니다.※ 지원 전 아래 내용을 꼭 확인해 주세요.42dot이 일하는 방식, 42dot Way 보러가기 →42dot만의 업무몰입 프로그램, Employee Engagement Program 보러가기 →

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We are looking for the bestAt 42dot, our AI Infrastructure Engineer manages the high-performance AI infrastructure orchestrating thousands of GPUs across multiple data centers. You will contribute to the scaling, monitoring, and operational optimization required to maintain a robust and world-class computing environment.ResponsibilitiesOperate and maintain a large-scale GPU cluster consisting of thousands of GPUs across multiple data centers using Kubernetes and Slurm.Monitor and diagnose failures across the GPU hardware and software stacks to ensure high availability and rapid recovery.Develop automation tools and scripts using Python or Shell to streamline repetitive infrastructure management tasks and improve operational efficiency.Manage GPU resource quotas and provide technical support to ML researchers to ensure optimal utilization of computing resources.Participate in the architectural design and performance tuning of distributed training environments for large-scale autonomous driving models.QualificationsStrong proficiency in Linux operating systems, including a solid understanding of kernel operations, process management, and system security.Practical experience with containerization technologies (Docker) and orchestration (Kubernetes), including building, managing, and troubleshooting containerized environments.Solid understanding of networking fundamentals, including TCP/IP and HTTP(S), with the ability to perform basic network troubleshooting.Ability to write clean and maintainable scripts in Python or Shell for automation and system administration.Logical approach to problem-solving with the persistence to identify and resolve root causes in complex, large-scale systems.Strong communication skills to effectively collaborate with cross-functional teams and external partners.Preferred QualificationsExperience in building observability stacks with Prometheus, Grafana, and Datadog for large-scale clusters.Experience in building or operating infrastructure on public cloud platforms such as AWS or GCP.Knowledge of the NVIDIA accelerated computing stack, including drivers, CUDA, and NCCL.Familiarity with the ML model training lifecycle and deep learning frameworks such as PyTorch or TensorFlow.Experience with large-scale workload managers or resource scheduling tools such as Kubernetes or Slurm.Familiarity with Infrastructure as Code (IaC) tools such as Terraform to manage complex infrastructure.Interview Process서류전형 - 온라인 코딩테스트 - 화상면접 (1시간 내외) - 대면면접 (3시간 내외) - 최종합격전형절차는 직무별로 다르게 운영될 수 있으며, 일정 및 상황에 따라 변동될 수 있습니다.전형일정 및 결과는 지원서에 등록하신 이메일로 개별 안내드립니다.Additional Information이력서 제출 시 주민등록번호, 가족관계, 혼인 여부, 연봉, 사진, 신체조건, 출신 지역 등 채용절차법상 요구 금지된 정보는 제외 부탁드립니다.모든 제출 파일은 30MB 이하의 PDF 양식으로 업로드를 부탁드립니다. (이력서 업로드 중 문제가 발생한다면 지원하시고자 하는 포지션의 URL과 함께 이력서를 recruit@42dot.ai으로 전송 부탁드립니다.)인터뷰 프로세스 종료 후 지원자의 동의하에 평판조회가 진행될 수 있습니다.국가보훈대상자 및 취업보호 대상자는 관계법령에 따라 우대합니다.장애인 고용 촉진 및 직업재활법에 따라 장애인 등록증 소지자를 우대합니다.42dot은 의뢰하지 않은 서치펌의 이력서를 받지 않으며, 요청하지 않은 이력서에 대해 수수료를 지불하지 않습니다.※ 지원 전 아래 내용을 꼭 확인해 주세요.42dot이 일하는 방식, 42dot Way 보러가기 →42dot만의 업무몰입 프로그램, Employee Engagement Program 보러가기 →

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Imagine having the power to stress-test an entire power grid against a hurricane before the clouds even gather. That is the reality we are creating at Neara. We use advanced machine learning to create engineering-grade, physics enabled digital twins of electricity grids across four continents, this helps asset owners understand their biggest challenges and bring the most viable solutions to life across millions of kilometres of infrastructure. By simulating extreme weather and structural stress at a network-wide scale, we empower the world’s largest utilities to pinpoint risks, optimise investments and build a more resilient global energy future. Our team is a collection of brilliant minds who are fanatical about making a tangible difference in the real world, utilising AI and machine learning to accelerate everything from data classification to complex scenario analysis. We have built a special culture where innovation thrives because everyone owns the mission and we need smart, creative people to help us scale this impact to every corner of the globe.ABOUT THE ROLEAs a Senior Software Engineer, you will be designing and implementing features in one of our engineering groups: Digitisation: generate digital twins from various data sources using a mix of machine learning, algorithms and work on tooling to correct bad extractions as fast as possible.Platform: provide the API surface for organisations to extract the most value out of the data hosted on the Neara platform. Work on our internal expression language and work with customers and other teams to identify the abstractions we need to provide.Design: take digital twins (or prospective designs) and analyse the viability of designs, from load analysis on infrastructure to identifying the resilience of the electric network to extreme weather events. WHAT YOU WILL DODigitisationDevelop and measure algorithmic/ML improvements to digital twin extraction.Improve monitoring to identify when our systems do a bad job of digital twin extraction (for example, distribution drift, misconfiguration).Develop tooling to quickly fix problems created by automated solutions.If you’d like to apply for a Machine Learning Engineer role in this group, please click here.PlatformDevelop the functionality of our internal platform by identifying common abstractions that can apply to many unique use cases.Data abstractions that allow users to semantically model and interact with their organisation's data.DesignDevelop solutions that provide designers the ability to simulate the structural forces on the network and the behaviour of the network in various weather scenarios.Develop CAD-like tooling to import engineering designs to develop networks or work with Digitisation to fit lidar and imagery to engineering designs in order to achieve better simulations.WHAT WE OFFERCompetitive salary & meaningful ESOPFully flexible working arrangements with a well-stocked office in RedfernRegular office eventsThe real benefit is working on a genuinely complex, innovative and industry-leading product, making a genuine difference in the world around us. To apply, please use the online application link below. Neara values diversity, belonging and equal employment opportunities. We encourage individuals from all backgrounds to apply. Please note that you will require current and unrestricted working rights to be considered for the role. Unfortunately, we are not in a position to offer visa sponsorship at this time.No agencies or third-party service providers, please.Questions? Email talent@neara.com.